Senior Software Engineer - Python
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Before you apply
LocationLahore, Punjab, Pakistan
Typefull-time
SenioritySenior
Experience3–6 yrs
DepartmentCluster Head
Company size501–1,000 people
PostedOct 28, 2026 · 1w ago
Verified live3d ago
At a glanceSummarised by Seekless from the posting.
3 to 6 years of professional software engineering experience, mostly in Python
Strong production experience with FastAPI plus Django and/or Flask, including async programming and REST API design
Hands-on experience building LLM-powered applications, including at least one RAG or agent-based system in production
Working knowledge of vector databases (Pinecone, Weaviate, Qdrant, pgvector) and embedding models
Solid data science fundamentals: data wrangling, statistics, model evaluation, and working with structured and unstructured data
Strong SQL skills (PostgreSQL) and experience with NoSQL stores and Redis
Hands-on cloud experience (AWS, GCP, or Azure) and containerization with Docker
Strong testing habits (pytest) and clean, typed Python (type hints, Pydantic)
Understanding of API security, OAuth 2.0, JWT, and responsible handling of sensitive data
Excellent communication skills, with the ability to explain complex AI concepts simply, run client demos, and confidently represent and sell our technical approach
Proven ability to lead projects and guide team members from proof of concept to production
Curiosity and the ability to evaluate and adopt new AI tools and models quickly
Experience with fine-tuning, prompt optimization, or model distillation
MLOps tools (MLflow, Kubeflow, SageMaker, Vertex AI, Bedrock)
Experience building MCP servers or multi-agent systems
Big data or streaming tools (Spark, Airflow, Kafka, dbt)
Familiarity with Node.js or TypeScript for full-stack collaboration
Published projects, research, Kaggle work, or open-source contributions in AI/ML
AWS, GCP, or Azure AI or ML certifications
Skills
Python
FastAPI
Django
Flask
LangChain
LangGraph
LlamaIndex
CrewAI
Claude Agent SDK
Pandas
NumPy
scikit-learn
PyTorch
TensorFlow
LangSmith
Langfuse
AWS
GCP
Azure
Docker
Kubernetes
Pinecone
Weaviate
Qdrant
pgvector
PostgreSQL
Redis
pytest
OAuth 2.0
JWT
MLflow
Kubeflow
SageMaker
Vertex AI
Bedrock
Spark
Airflow
Kafka
dbt
Node.js
TypeScript
Responsibilities
•
Design, build, and scale backend services and APIs using Python with FastAPI, Django, and Flask
•
Build and ship agentic AI systems: multi-step agents, tool calling, MCP integrations, and orchestration with frameworks like LangChain/LangGraph, LlamaIndex, CrewAI, or the Claude Agent SDK
•
Develop RAG pipelines, including document ingestion, chunking, embeddings, vector databases, retrieval tuning, and evaluation
•
Integrate and optimize LLMs (OpenAI, Anthropic Claude, Gemini, open-source models) for accuracy, latency, and cost
•
Build data pipelines, analytics, and ML workflows using Pandas, NumPy, scikit-learn, and PyTorch or TensorFlow
•
Set up LLM evaluation, guardrails, monitoring, and observability (LangSmith, Langfuse, or similar) for production AI systems
•
Deploy and operate services on AWS, GCP, or Azure with Docker, Kubernetes, and CI/CD pipelines
•
Lead technical design, break down work, mentor engineers, and set code-quality and AI-engineering standards
•
Present AI solutions, demos, and technical roadmaps to clients, stakeholders, and leadership
•
Take part in on-call rotations and production incident response
Requirements
•
3 to 6 years of professional software engineering experience, mostly in Python
•
Strong production experience with FastAPI plus Django and/or Flask, including async programming and REST API design
•
Hands-on experience building LLM-powered applications, including at least one RAG or agent-based system in production
•
Working knowledge of vector databases (Pinecone, Weaviate, Qdrant, pgvector) and embedding models
•
Solid data science fundamentals: data wrangling, statistics, model evaluation, and working with structured and unstructured data
•
Strong SQL skills (PostgreSQL) and experience with NoSQL stores and Redis
•
Hands-on cloud experience (AWS, GCP, or Azure) and containerization with Docker
•
Strong testing habits (pytest) and clean, typed Python (type hints, Pydantic)
•
Understanding of API security, OAuth 2.0, JWT, and responsible handling of sensitive data
•
Excellent communication skills, with the ability to explain complex AI concepts simply, run client demos, and confidently represent and sell our technical approach
•
Proven ability to lead projects and guide team members from proof of concept to production
•
Curiosity and the ability to evaluate and adopt new AI tools and models quickly
Nice to have
Nice to have
•
Experience with fine-tuning, prompt optimization, or model distillation
•
MLOps tools (MLflow, Kubeflow, SageMaker, Vertex AI, Bedrock)
•
Experience building MCP servers or multi-agent systems
•
Big data or streaming tools (Spark, Airflow, Kafka, dbt)
•
Familiarity with Node.js or TypeScript for full-stack collaboration
•
Published projects, research, Kaggle work, or open-source contributions in AI/ML
•
AWS, GCP, or Azure AI or ML certifications